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Register a new userTesting the Gaussianity of the COBE-DMR data with spherical wavelets
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We investigate the Gaussianity of the 4-year COBE-DMR data (in HEALPix pixelisation) using an analysis based on spherical Haar wavelets. We use all the pixels lying outside the Galactic cut and compute the skewness, kurtosis and scale-scale correlation spectra for the wavelet coefficients at each scale. We also take into account the sensitivity of the method to the orientation of the input signal. We find a detection of non-Gaussianity at $> 99$ per cent level in just one of our statistics. Taking into account the total number of statistics computed, we estimate that the probability of obtaining such a detection by chance for an underlying Gaussian field is 0.69. Therefore, we conclude that the spherical wavelet technique shows no strong evidence of non-Gaussianity in the COBE-DMR data.
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We present an analysis of the Gaussianity of the 4-year COBE-DMR data (in HEALPix pixelisation) based on spherical wavelets. The skewness, kurtosis and scale-scale correlation spectra are computed from the detail wavelet coefficients at each scale. The sensitivity of the method to the orientation of the data is also taken into account. We find a single detection of non-Gaussianity at the $>99%$ confidence level in one of our statistics. We use Monte-Carlo simulations to assess the statistical significance of this detection and find that the probability of obtaining such a detection by chance for an underlying Gaussian field is as high as 0.69. Therefore, our analysis does not show evidence of non-Gaussianity in the COBE-DMR data.
We derive an optimal linear filter to suppress the noise from the COBE DMR sky maps for a given power spectrum. We then apply the filter to the first-year DMR data, after removing pixels within $20^circ$ of the Galactic plane from the data. The filtered data have uncertainties 12 times smaller than the noise level of the raw data. We use the formalism of constrained realizations of Gaussian random fields to assess the uncertainty in the filtered sky maps. In addition to improving the signal-to-noise ratio of the map as a whole, these techniques allow us to recover some information about the CMB anisotropy in the missing Galactic plane region. From these maps we are able to determine which hot and cold spots in the data are statistically significant, and which may have been produced by noise. In addition, the filtered maps can be used for comparison with other experiments on similar angular scales.
More than a dozen papers analyzing the COBE data have now appeared. We review the different techniques and compare them to a ``brute force likelihood analysis where we invert the full 4038 x 4038 Galaxy-cut pixel covariance matrix. This method is optimal in the sense of producing minimal error bars, and is a useful reference point for comparing other analysis techniques. Our maximum-likelihood estimate of the spectral index and normalization are n=1.15 (0.95) and Q=18.2 (21.3) micro-Kelvin including (excluding) the quadrupole. Marginalizing over the normalization C_9, we obtain n=1.10 +/- 0.29 (n=0.90 +/- 0.32). When we compare these results with those of the various techniques that involve a linear ``compression of the data, we find that the latter are all consistent with the brute-force analysis and have error bars that are nearly as small as the minimal error bars. We therefore conclude that the data compressions involved in these techniques do indeed retain most of the useful cosmological information.
We present an application of the fast Independent Component Analysis method to the COBE-DMR 4yr data. Although the signal-to-noise ratio in the COBE-DMR data is typically $sim 1$, the approach is able to extract the CMB signal with high confidence when working at high galactic latitudes. The reconstructed CMB map shows the expected frequency scaling of the CMB. We fit the resulting CMB component for the rms quadrupole normalisation Qrms and primordial spectral index n and find results in excellent agreement with those derived from the minimum-noise combination of the 90 and 53 GHz DMR channels without galactic emission correction. Including additional channels (priors) such as the Haslam map of radio emission at 408 MHz and the DIRBE 140um map of galactic infra-red emission, the FastICA algorithm is able to both detect galactic foreground emission and separate it from the dominant CMB signal. Fitting the resulting CMB component for Qrms and n we find good agreement with the results from Gorski et al.(1996) in which the galactic emission has been taken into account by subtracting that part of the DMR signal observed to be correlated with these galactic template maps. We further investigate the ability of FastICA to evaluate the extent of foreground contamination in the COBE-DMR data. We include an all-sky Halpha survey (Dickinson, Davies & Davis 2003) to determine a reliable free-free template. In particular we find that, after subtraction of the thermal dust emission predicted by the Finkbeiner, Davis & Schlegel (1999) model 7, this component is the dominant foreground emission at 31.5 GHz. This indicates the presence of an anomalous dust correlated component which is well fitted by a power law spectral shape $ u^{-beta}$ with $beta sim 2.5$ in agreement with Banday et al. (2003).
The first two years of COBE DMR observations of the CMB anisotropy are analyzed and compared with our previously published first year results. The results are consistent, but the addition of the second year of data increases the precision and accuracy of the detected CMB temperature fluctuations. The two-year 53 GHz data are characterized by RMS temperature fluctuations of DT=44+/-7 uK at 7 degrees and DT=30.5+/-2.7 uK at 10 degrees angular resolution. The 53X90 GHz cross-correlation amplitude at zero lag is C(0)^{1/2}=36+/-5 uK (68%CL) for the unsmoothed 7 degree DMR data. A likelihood analysis of the cross correlation function, including the quadrupole anisotropy, gives a most likely quadrupole-normalized amplitude Q_{rms-PS}=12.4^{+5.2}_{-3.3} uK (68% CL) and a spectral index n=1.59^{+0.49}_{-0.55} for a power law model of initial density fluctuations, P(k)~k^n. With n fixed to 1.0 the most likely amplitude is 17.4 +/-1.5 uK (68% CL). Excluding the quadrupole anisotropy we find Q_{rms-PS}= 16.0^{+7.5}_{-5.2} uK (68% CL), n=1.21^{+0.60}_{-0.55}, and, with n fixed to 1.0 the most likely amplitude is 18.2+/-1.6 uK (68% CL). Monte Carlo simulations indicate that these derived estimates of n may be biased by ~+0.3 (with the observed low value of the quadrupole included in the analysis) and {}~+0.1 (with the quadrupole excluded). Thus the most likely bias-corrected estimate of n is between 1.1 and 1.3. Our best estimate of the dipole from the two-year DMR data is 3.363+/-0.024 mK towards Galactic coordinates (l,b)= (264.4+/-0.2 degrees, +48.1+/-0.4 degrees), and our best estimate of the RMS quadrupole amplitude in our sky is 6+/-3 uK.
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